Cyrene/backend/gateway/internal/handler/image_handler.go

package handler

import (
	"bytes"
	"encoding/base64"
	"encoding/json"
	"fmt"
	"image"
	"image/color"
	_ "image/gif"
	_ "image/jpeg"
	_ "image/png"
	"io"
	"git.yeij.top/AskaEth/Cyrene/pkg/logger"
	"net/http"
	"os"
	"sort"
	"strings"

	"github.com/gin-gonic/gin"

	"git.yeij.top/AskaEth/Cyrene/gateway/internal/config"
	"git.yeij.top/AskaEth/Cyrene/gateway/internal/middleware"
	"git.yeij.top/AskaEth/Cyrene/gateway/internal/store"
)

// ImageHandler 图片分析处理器
type ImageHandler struct {
	cfg       *config.Config
	fileStore *store.FileStore
}

// NewImageHandler 创建图片分析处理器
func NewImageHandler(cfg *config.Config, fileStore *store.FileStore) *ImageHandler {
	return &ImageHandler{
		cfg:       cfg,
		fileStore: fileStore,
	}
}

// ImageAnalysis 图片分析结果
type ImageAnalysis struct {
	Format      string       `json:"format"`
	Width       int          `json:"width"`
	Height      int          `json:"height"`
	FileSize    int64        `json:"file_size"`
	Description string       `json:"description"`
	TopColors   []ColorInfo  `json:"top_colors,omitempty"`
	EXIF        map[string]string `json:"exif,omitempty"`
	AnalyzedBy  string       `json:"analyzed_by"` // "openai_vision" | "local"
}

// ColorInfo 颜色信息
type ColorInfo struct {
	Hex       string  `json:"hex"`
	Percent   float64 `json:"percent"`
}

// AnalyzeRequestBody 分析请求体
type AnalyzeRequestBody struct {
	FileID string `json:"file_id"`
}

// ========== POST /api/v1/images/analyze ==========

// Analyze 分析上传的图片 (multipart/form-data 或 JSON)
func (h *ImageHandler) Analyze(c *gin.Context) {
	userID := middleware.GetUserID(c)

	// 尝试 JSON body: {"file_id": "xxx"}
	contentType := c.GetHeader("Content-Type")
	if strings.HasPrefix(contentType, "application/json") {
		var body AnalyzeRequestBody
		if err := c.ShouldBindJSON(&body); err != nil || body.FileID == "" {
			c.JSON(http.StatusBadRequest, gin.H{"error": "缺少 file_id 字段", "errorType": "invalid_request"})
			return
		}
		h.analyzeByFileID(c, userID, body.FileID)
		return
	}

	// 尝试 multipart/form-data: 直接上传图片分析
	file, header, err := c.Request.FormFile("file")
	if err != nil {
		// 也尝试 "image" 字段名
		file, header, err = c.Request.FormFile("image")
		if err != nil {
			c.JSON(http.StatusBadRequest, gin.H{"error": "未找到图片文件 (使用 file 或 image 字段)", "errorType": "missing_file"})
			return
		}
	}
	defer file.Close()

	h.analyzeUploadedFile(c, userID, file, header.Filename, header.Size)
}

// ========== GET /api/v1/images/analyze/:file_id ==========

// AnalyzeByID 对已上传的文件进行分析
func (h *ImageHandler) AnalyzeByID(c *gin.Context) {
	userID := middleware.GetUserID(c)
	fileID := c.Param("file_id")
	if fileID == "" {
		c.JSON(http.StatusBadRequest, gin.H{"error": "缺少 file_id", "errorType": "invalid_request"})
		return
	}
	h.analyzeByFileID(c, userID, fileID)
}

// analyzeByFileID 根据文件ID分析已存储的图片
func (h *ImageHandler) analyzeByFileID(c *gin.Context, userID, fileID string) {
	if h.fileStore == nil {
		c.JSON(http.StatusServiceUnavailable, gin.H{"error": "文件存储不可用", "errorType": "service_unavailable"})
		return
	}

	f, err := h.fileStore.GetFile(fileID)
	if err != nil {
		logger.Printf("[ImageHandler] 查询文件失败: %v", err)
		c.JSON(http.StatusInternalServerError, gin.H{"error": "查询文件失败", "errorType": "db_error"})
		return
	}
	if f == nil {
		c.JSON(http.StatusNotFound, gin.H{"error": "文件不存在", "errorType": "file_not_found"})
		return
	}
	if f.UserID != userID && !f.IsPublic {
		c.JSON(http.StatusForbidden, gin.H{"error": "无权访问此文件", "errorType": "access_denied"})
		return
	}
	if !isImageType(f.MimeType) {
		c.JSON(http.StatusBadRequest, gin.H{"error": "文件不是图片类型: " + f.MimeType, "errorType": "unsupported_type"})
		return
	}

	result, err := h.analyzeImage(f.StoredPath, f.MimeType, f.Size)
	if err != nil {
		logger.Printf("[ImageHandler] 图片分析失败: %v", err)
		c.JSON(http.StatusInternalServerError, gin.H{"error": "图片分析失败: " + err.Error(), "errorType": "analysis_error"})
		return
	}

	c.JSON(http.StatusOK, result)
}

// analyzeUploadedFile 分析直接上传的图片文件
func (h *ImageHandler) analyzeUploadedFile(c *gin.Context, userID string, file io.Reader, filename string, fileSize int64) {
	// 检查文件大小 (10MB 限制)
	const maxImageSize = 10 * 1024 * 1024
	if fileSize > maxImageSize {
		c.JSON(http.StatusBadRequest, gin.H{"error": "图片大小超过限制 (最大 10MB)", "errorType": "file_too_large"})
		return
	}

	// 读取文件到内存
	data, err := io.ReadAll(file)
	if err != nil {
		c.JSON(http.StatusInternalServerError, gin.H{"error": "读取图片失败", "errorType": "read_error"})
		return
	}

	// 检测格式
	_, format, err := image.DecodeConfig(bytes.NewReader(data))
	if err != nil {
		c.JSON(http.StatusBadRequest, gin.H{"error": "无法解码图片: " + err.Error(), "errorType": "decode_error"})
		return
	}

	mimeType := "image/" + format
	supportedFormats := map[string]bool{
		"image/jpeg": true,
		"image/png":  true,
		"image/gif":  true,
	}
	if !supportedFormats[mimeType] {
		// 允许所有 image/* 格式，但只对常见格式做深入分析
	}

	// 写入临时文件进行分析
	tmpFile, err := os.CreateTemp("", "cyrene-image-*."+format)
	if err != nil {
		c.JSON(http.StatusInternalServerError, gin.H{"error": "创建临时文件失败", "errorType": "server_error"})
		return
	}
	defer os.Remove(tmpFile.Name())
	defer tmpFile.Close()

	if _, err := tmpFile.Write(data); err != nil {
		c.JSON(http.StatusInternalServerError, gin.H{"error": "写入临时文件失败", "errorType": "server_error"})
		return
	}

	result, err := h.analyzeImage(tmpFile.Name(), mimeType, int64(len(data)))
	if err != nil {
		logger.Printf("[ImageHandler] 图片分析失败: %v", err)
		c.JSON(http.StatusInternalServerError, gin.H{"error": "图片分析失败: " + err.Error(), "errorType": "analysis_error"})
		return
	}

	c.JSON(http.StatusOK, result)
}

// analyzeImage 核心分析逻辑：先尝试 OpenAI Vision，失败则降级到本地分析
func (h *ImageHandler) analyzeImage(filePath, mimeType string, fileSize int64) (*ImageAnalysis, error) {
	// 如果配置了 OpenAI API Key，尝试使用 Vision API
	apiKey := h.cfg.LLMAPIKey
	if apiKey != "" {
		result, err := h.analyzeWithOpenAIVision(filePath, mimeType)
		if err == nil {
			return result, nil
		}
		logger.Printf("[ImageHandler] OpenAI Vision 分析失败，降级到本地分析: %v", err)
	}

	// 降级到本地分析
	return analyzeImageLocally(filePath, mimeType, fileSize)
}

// analyzeWithOpenAIVision 使用 OpenAI Vision API 分析图片
func (h *ImageHandler) analyzeWithOpenAIVision(filePath, mimeType string) (*ImageAnalysis, error) {
	// 读取图片并编码为 base64
	data, err := os.ReadFile(filePath)
	if err != nil {
		return nil, fmt.Errorf("读取图片文件失败: %w", err)
	}

	base64Data := base64.StdEncoding.EncodeToString(data)
	dataURL := fmt.Sprintf("data:%s;base64,%s", mimeType, base64Data)

	// 获取本地基本信息
	localInfo, err := analyzeImageLocally(filePath, mimeType, int64(len(data)))
	if err != nil {
		localInfo = &ImageAnalysis{}
	}

	// 构建 OpenAI Vision API 请求
	reqBody := map[string]interface{}{
		"model": h.cfg.LLMModel,
		"messages": []map[string]interface{}{
			{
				"role": "user",
				"content": []map[string]interface{}{
					{
						"type": "text",
						"text": "请详细描述这张图片的内容。用中文回答。请描述：1) 图片中的主要物体/人物 2) 场景/环境 3) 颜色和色调 4) 文字内容（如果有）5) 整体氛围和风格。请尽可能详细。",
					},
					{
						"type": "image_url",
						"image_url": map[string]string{
							"url": dataURL,
						},
					},
				},
			},
		},
		"max_tokens": 500,
	}

	jsonBody, err := json.Marshal(reqBody)
	if err != nil {
		return nil, fmt.Errorf("序列化请求失败: %w", err)
	}

	apiURL := strings.TrimRight(h.cfg.LLMAPIURL, "/") + "/chat/completions"
	httpReq, err := http.NewRequest("POST", apiURL, bytes.NewReader(jsonBody))
	if err != nil {
		return nil, fmt.Errorf("创建请求失败: %w", err)
	}
	httpReq.Header.Set("Content-Type", "application/json")
	httpReq.Header.Set("Authorization", "Bearer "+h.cfg.LLMAPIKey)

	httpClient := &http.Client{}
	resp, err := httpClient.Do(httpReq)
	if err != nil {
		return nil, fmt.Errorf("API 请求失败: %w", err)
	}
	defer resp.Body.Close()

	body, _ := io.ReadAll(resp.Body)
	if resp.StatusCode != http.StatusOK {
		return nil, fmt.Errorf("API 返回错误 (%d): %s", resp.StatusCode, string(body))
	}

	var result struct {
		Choices []struct {
			Message struct {
				Content string `json:"content"`
			} `json:"message"`
		} `json:"choices"`
	}
	if err := json.Unmarshal(body, &result); err != nil {
		return nil, fmt.Errorf("解析响应失败: %w", err)
	}

	var description string
	if len(result.Choices) > 0 {
		description = result.Choices[0].Message.Content
	}

	return &ImageAnalysis{
		Format:      localInfo.Format,
		Width:       localInfo.Width,
		Height:      localInfo.Height,
		FileSize:    localInfo.FileSize,
		Description: description,
		TopColors:   localInfo.TopColors,
		EXIF:        localInfo.EXIF,
		AnalyzedBy:  "openai_vision",
	}, nil
}

// analyzeImageLocally 使用 Go 标准库进行本地图片分析
func analyzeImageLocally(filePath, mimeType string, fileSize int64) (*ImageAnalysis, error) {
	// 1. 读取文件
	data, err := os.ReadFile(filePath)
	if err != nil {
		return nil, fmt.Errorf("读取文件失败: %w", err)
	}

	// 2. 解码图片
	img, format, err := image.Decode(bytes.NewReader(data))
	if err != nil {
		return nil, fmt.Errorf("解码图片失败: %w", err)
	}

	// 3. 获取尺寸
	bounds := img.Bounds()
	width := bounds.Dx()
	height := bounds.Dy()

	// 4. 计算颜色直方图 (采样像素)
	topColors := computeColorHistogram(img, 5)

	// 5. 读取 EXIF (简单实现: 仅 JPEG)
	exif := extractEXIF(data, format)

	// 6. 生成描述文本
	description := generateLocalDescription(format, width, height, fileSize, topColors)

	return &ImageAnalysis{
		Format:      format,
		Width:       width,
		Height:      height,
		FileSize:    fileSize,
		Description: description,
		TopColors:   topColors,
		EXIF:        exif,
		AnalyzedBy:  "local",
	}, nil
}

// computeColorHistogram 计算颜色直方图，返回 top N 颜色
func computeColorHistogram(img image.Image, topN int) []ColorInfo {
	bounds := img.Bounds()
	width := bounds.Dx()
	height := bounds.Dy()

	// 采样间隔：每 step 个像素采样一个
	step := 1
	totalPixels := width * height
	if totalPixels > 10000 {
		step = (width * height) / 10000
		if step < 1 {
			step = 1
		}
	}

	colorCount := make(map[string]int)
	sampledCount := 0

	for y := bounds.Min.Y; y < bounds.Max.Y; y += step {
		for x := bounds.Min.X; x < bounds.Max.X; x += step {
			r, g, b, _ := img.At(x, y).RGBA()
			// 量化到 8-bit 并聚类（每 32 级一分组，减少颜色种类）
			qr := int(r>>8) / 32
			qg := int(g>>8) / 32
			qb := int(b>>8) / 32
			key := fmt.Sprintf("%02d_%02d_%02d", qr, qg, qb)
			colorCount[key]++
			sampledCount++
		}
	}

	if sampledCount == 0 {
		return nil
	}

	// 排序取 topN
	type kv struct {
		key   string
		count int
	}
	var sorted []kv
	for k, v := range colorCount {
		sorted = append(sorted, kv{k, v})
	}
	sort.Slice(sorted, func(i, j int) bool {
		return sorted[i].count > sorted[j].count
	})

	result := make([]ColorInfo, 0, topN)
	for i := 0; i < topN && i < len(sorted); i++ {
		var qr, qg, qb int
		fmt.Sscanf(sorted[i].key, "%d_%d_%d", &qr, &qg, &qb)
		// 量化组的中间值
		r := qr*32 + 16
		g := qg*32 + 16
		b := qb*32 + 16
		hex := fmt.Sprintf("#%02X%02X%02X", r, g, b)
		pct := float64(sorted[i].count) / float64(sampledCount) * 100
		result = append(result, ColorInfo{
			Hex:     hex,
			Percent: pct,
		})
	}

	return result
}

// extractEXIF 简单提取 JPEG EXIF 信息
func extractEXIF(data []byte, format string) map[string]string {
	if format != "jpeg" {
		return nil
	}

	exif := make(map[string]string)

	// 查找 EXIF 标记 (0xFFE1)
	for i := 0; i < len(data)-4; i++ {
		if data[i] == 0xFF && data[i+1] == 0xE1 {
			if i+10 >= len(data) {
				break
			}
			// 验证 EXIF 标识 "Exif\0\0"
			if string(data[i+4:i+10]) != "Exif\x00\x00" {
				continue
			}

			exifStart := i + 10
			if exifStart+8 >= len(data) {
				break
			}

			// 判断字节序
			var bigEndian bool
			if data[exifStart] == 'M' && data[exifStart+1] == 'M' {
				bigEndian = true
			} else if data[exifStart] == 'I' && data[exifStart+1] == 'I' {
				bigEndian = false
			} else {
				break
			}

			// 读取 IFD0
			tiffStart := exifStart
			readUint16 := func(offset int) uint16 {
				if offset+2 > len(data) {
					return 0
				}
				if bigEndian {
					return uint16(data[offset])<<8 | uint16(data[offset+1])
				}
				return uint16(data[offset+1])<<8 | uint16(data[offset])
			}

			ifd0Offset := int(readUint16(tiffStart + 4))
			if ifd0Offset < 8 {
				break
			}
			ifd0Addr := tiffStart + ifd0Offset
			if ifd0Addr+2 >= len(data) {
				break
			}

			numEntries := int(readUint16(ifd0Addr))
			entryAddr := ifd0Addr + 2

			// 常见 EXIF 标签
			tagNames := map[uint16]string{
				0x010F: "Make",
				0x0110: "Model",
				0x0112: "Orientation",
				0x0132: "DateTime",
				0x829A: "ExposureTime",
				0x829D: "FNumber",
				0x8827: "ISO",
				0x9003: "DateTimeOriginal",
				0x920A: "FocalLength",
			}

			for j := 0; j < numEntries && entryAddr+12 <= len(data); j++ {
				tag := readUint16(entryAddr)
				dataType := readUint16(entryAddr + 2)
				dataCount := int(readUint16(entryAddr + 4))

				entryAddr += 12

				if name, ok := tagNames[tag]; ok {
					valueLen := dataCount
					switch dataType {
					case 2: // ASCII
						valueLen = dataCount
					case 3, 4: // SHORT, LONG
						valueLen = dataCount * 2
					case 5: // RATIONAL
						valueLen = dataCount * 8
					}

					if valueLen <= 4 {
						// 值在 tag 自身中
						valData := data[entryAddr-4 : entryAddr]
						valStr := extractASCIIValue(valData, dataType, dataCount, bigEndian)
						if valStr != "" {
							exif[name] = valStr
						}
					}
				}
			}

			break // 只处理第一个 EXIF 块
		}
	}

	if len(exif) == 0 {
		return nil
	}
	return exif
}

// extractASCIIValue 从 EXIF 数据中提取 ASCII 值
func extractASCIIValue(data []byte, dataType uint16, count int, bigEndian bool) string {
	switch dataType {
	case 2: // ASCII string
		s := string(data)
		if idx := strings.IndexByte(s, 0); idx >= 0 {
			s = s[:idx]
		}
		return s
	case 3: // SHORT
		if len(data) >= 2 {
			var val uint16
			if bigEndian {
				val = uint16(data[0])<<8 | uint16(data[1])
			} else {
				val = uint16(data[1])<<8 | uint16(data[0])
			}
			return fmt.Sprintf("%d", val)
		}
	case 5: // RATIONAL
		// 简化处理：返回原始字节
		return ""
	}
	return ""
}

// generateLocalDescription 生成本地图片描述文本
func generateLocalDescription(format string, width, height int, fileSize int64, topColors []ColorInfo) string {
	var sb strings.Builder

	formatNames := map[string]string{
		"jpeg": "JPEG",
		"jpg":  "JPEG",
		"png":  "PNG",
		"gif":  "GIF",
		"webp": "WebP",
		"bmp":  "BMP",
	}

	formatName := strings.ToUpper(format)
	if name, ok := formatNames[strings.ToLower(format)]; ok {
		formatName = name
	}

	sb.WriteString(fmt.Sprintf("这是一张 %s 格式的图片，", formatName))
	sb.WriteString(fmt.Sprintf("分辨率为 %d×%d 像素，", width, height))
	sb.WriteString(fmt.Sprintf("文件大小为 %s。", formatFileSize(fileSize)))

	// 判断大致比例
	ratio := float64(width) / float64(height)
	if ratio > 1.8 {
		sb.WriteString("图片呈宽幅横幅比例。")
	} else if ratio < 0.6 {
		sb.WriteString("图片呈竖幅比例。")
	} else if ratio > 1.2 {
		sb.WriteString("图片接近横向画幅。")
	} else if ratio < 0.8 {
		sb.WriteString("图片接近纵向画幅。")
	} else {
		sb.WriteString("图片接近正方形比例。")
	}

	// 描述主要颜色
	if len(topColors) > 0 {
		sb.WriteString(" 主要色调为")
		for i, c := range topColors {
			if i > 0 {
				if i == len(topColors)-1 {
					sb.WriteString(" 和 ")
				} else {
					sb.WriteString("、")
				}
			}
			colorName := getColorName(c.Hex)
			sb.WriteString(fmt.Sprintf("%s(%s, %.0f%%)", colorName, c.Hex, c.Percent))
		}
		sb.WriteString("。")
	}

	return sb.String()
}

// formatFileSize 格式化文件大小
func formatFileSize(size int64) string {
	if size < 1024 {
		return fmt.Sprintf("%d B", size)
	}
	if size < 1024*1024 {
		return fmt.Sprintf("%.1f KB", float64(size)/1024)
	}
	return fmt.Sprintf("%.1f MB", float64(size)/(1024*1024))
}

// getColorName 根据 hex 颜色获取中文颜色名
func getColorName(hex string) string {
	if len(hex) < 7 {
		return hex
	}
	var r, g, b uint8
	fmt.Sscanf(hex, "#%02X%02X%02X", &r, &g, &b)

	// 灰度判断
	if absDiff(r, g) < 20 && absDiff(g, b) < 20 && absDiff(r, b) < 20 {
		if r < 40 {
			return "黑色"
		}
		if r < 100 {
			return "深灰色"
		}
		if r < 180 {
			return "灰色"
		}
		if r < 230 {
			return "浅灰色"
		}
		return "白色"
	}

	// HSL 近似判断色调
	maxC := max(r, max(g, b))
	minC := min(r, min(g, b))
	delta := maxC - minC

	if delta < 30 {
		if maxC < 60 {
			return "暗色"
		}
		if maxC > 200 {
			return "浅色"
		}
		return "中性色"
	}

	var hue string
	switch {
	case r == maxC:
		if g >= b {
			hue = "红色"
		} else {
			hue = "品红色"
		}
	case g == maxC:
		if b >= r {
			hue = "绿色"
		} else {
			hue = "黄绿色"
		}
	default:
		if r >= g {
			hue = "紫红色"
		} else {
			hue = "蓝色"
		}
	}

	// 亮度修饰
	if maxC < 80 {
		hue = "深" + hue
	} else if minC > 200 {
		hue = "浅" + hue
	}

	return hue
}

func absDiff(a, b uint8) int {
	if a > b {
		return int(a - b)
	}
	return int(b - a)
}

func max(a, b uint8) uint8 {
	if a > b {
		return a
	}
	return b
}

func min(a, b uint8) uint8 {
	if a < b {
		return a
	}
	return b
}

// ========== color.RGBA → string 辅助 ==========

var _ = color.RGBA{} // 确保 color 包被使用